Reagent Tracker™ Platform Verifies and Provides Audit Trails for the Error-Free Implementation of T-Cell ImmunoSpot® Assays.

ELISPOT and FluoroSpot assays, collectively called ImmunoSpot assays, permit to reliable detection of rare antigen-specific T cells in freshly isolated cell material, such as peripheral blood mononuclear cells (PBMC). Establishing their frequency within all PBMC permits to assess the magnitude of antigen-specific T-cell immunity; the simultaneous measurement of their cytokine signatures reveals these T-cells' lineage and effector functions, that is, the quality of T-cell-mediated immunity. Because of their unparalleled sensitivity, ease of implementation, robustness, and frugality in PBMC utilization, T-cell ImmunoSpot assays are increasingly becoming part of the standard immune monitoring repertoire. For regulated workflows, stringent audit trails of the data generated are a requirement. While this has been fully accomplished for the analysis of T-cell ImmunoSpot assay results, such are missing for the wet laboratory implementation of the actual test performed. Here we introduce a solution for enhancing and verifying the error-free implementation of T-cell ImmunoSpot assays.

Artificial Intelligence-Based Counting Algorithm Enables Accurate and Detailed Analysis of the Broad Spectrum of Spot Morphologies Observed in Antigen-Specific B-Cell ELISPOT and FluoroSpot Assays.

Antigen-specific B-cell ELISPOT and multicolor FluoroSpot assays, in which the membrane-bound antigen itself serves as the capture reagent for the antibodies that B cells secrete, inherently result in a broad range of spot sizes and intensities. The diversity of secretory footprint morphologies reflects the polyclonal nature of the antigen-specific B cell repertoire, with individual antibody-secreting B cells in the test sample differing in their affinity for the antigen, fine epitope specificity, and activation/secretion kinetics. To account for these heterogeneous spot morphologies, and to eliminate the need for setting up subjective counting parameters well-by-well, CTL introduces here its cutting-edge deep learning-based IntelliCount™ algorithm within the ImmunoSpot® Studio Software Suite, which integrates CTL's proprietary deep neural network. Here, we report detailed analyses of spots with a broad range of morphologies that were challenging to analyze using standard parameter-based counting approaches. IntelliCount™, especially in conjunction with high dynamic range (HDR) imaging, permits the extraction of accurate, high-content information of such spots, as required for assessing the affinity distribution of an antigen-specific memory B-cell repertoire ex vivo. IntelliCount™ also extends the range in which the number of antibody-secreting B cells plated and spots detected follow a linear function; that is, in which the frequencies of antigen-specific B cells can be accurately established. Introducing high-content analysis of secretory footprints in B-cell ELISPOT/FluoroSpot assays, therefore, fundamentally enhances the depth in which an antigen-specific B-cell repertoire can be studied using freshly isolated or cryopreserved primary cell material, such as peripheral blood mononuclear cells.

Multi-Color FLUOROSPOT Counting Using ImmunoSpot® Fluoro-X™ Suite.

Multi-color FLUOROSPOT assays for simultaneous detection of several T-cell cytokines and/or classes/sub-classes of immunoglobulins secreted by B cells have recently become a major new avenue of development of ELISPOT technology. Advances in assay techniques and the availability of commercial test kits stimulated development of multi-color FLUOROSPOT data analysis platforms. The ImmunoSpot® Fluoro-X™ Software Suite was developed by CTL as an integrated data acquisition, analysis, and management solution for automated high-throughput processing of multi-color T- and B-cell FLUOROSPOT assay plates. The Fluoro-X™ software counting module is based on SmartSpot™/AutoGate™ technologies and utilizes CTL's Center of Mass Distance algorithm for the detection of multi-color spots. The Fluoro-X™ software provides an objective, user error-free means for analyzing multi-color FLUOROSPOT data. An integrated quality control module, with optional GLP and CFR Part 11 compliant package and role-based security, enables data validation, review, and approval with complete audit trails. The extensive multi-format data output and presentation capabilities of the Fluoro-X™ software allow further analysis of FLUOROSPOT data using any commercial flow cytometry software and facilitate the generation of professional reports and presentation. In this article, we present a detailed step-by-step workflow for the analysis of a human four-color IFN-γ, IL-2, TNF-α, and GzB antigen-specific T-cell assay using the Fluoro-X Software Suite.

Reagent Tracker Dyes Permit Quality Control for Verifying Plating Accuracy in ELISPOT Tests.

ELISPOT assays enable the detection of the frequency of antigen-specific T cells in the blood by measuring the secretion of cytokines, or combinations of cytokines, in response to antigenic challenges of a defined population of PBMC. As such, these assays are suited to establish the magnitude and quality of T cell immunity in infectious, allergic, autoimmune and transplant settings, as well as for measurements of anti-tumor immunity. The simplicity, robustness, cost-effectiveness and scalability of ELISPOT renders it suitable for regulated immune monitoring. In response to the regulatory requirements of clinical and pre-clinical immune monitoring trials, tamper-proof audit trails have been introduced to all steps of ELISPOT analysis: from capturing the raw images of assay wells and counting of spots, to all subsequent quality control steps involved in count verification. A major shortcoming of ELISPOT and other related cellular assays is presently the lack of audit trails for the wet laboratory part of the assay, in particular, the assurance that no pipetting errors have occurred during the plating of antigens and cells. Here, we introduce a dye-based reagent tracking platform that fills this gap, thereby increasing the transparency and documentation of ELISPOT test results.

Multiplexing T- and B-Cell FLUOROSPOT Assays: Experimental Validation of the Multi-Color ImmunoSpot® Software Based on Center of Mass Distance Algorithm.

Over the past decade, ELISPOT has become a highly implemented mainstream assay in immunological research, immune monitoring, and vaccine development. Unique single cell resolution along with high throughput potential sets ELISPOT apart from flow cytometry, ELISA, microarray- and bead-based multiplex assays. The necessity to unambiguously identify individual T and B cells that do, or do not co-express certain analytes, including polyfunctional cytokine producing T cells has stimulated the development of multi-color ELISPOT assays. The success of these assays has also been driven by limited sample/cell availability and resource constraints with reagents and labor. There are few commercially available test kits and instruments available at present for multi-color FLUOROSPOT. Beyond commercial descriptions of competing systems, little is known about their accuracy in experimental settings detecting individual cells that secrete multiple analytes vs. random overlays of spots. Here, we present a theoretical and experimental validation study for three and four color T- and B-cell FLUOROSPOT data analysis. The ImmunoSpot® Fluoro-X™ analysis system we used includes an automatic image acquisition unit that generates individual color images free of spectral overlaps and multi-color spot counting software based on the maximal allowed distance between centers of spots of different colors or Center of Mass Distance (COMD). Using four color B-cell FLUOROSPOT for IgM, IgA, IgG1, IgG3; and three/four color T-cell FLUOROSPOT for IL-2, IFN-γ, TNF-α, and GzB, in serial dilution experiments, we demonstrate the validity and accuracy of Fluoro-X™ multi-color spot counting algorithms. Statistical predictions based on the Poisson spatial distribution, coupled with scrambled image counting, permit objective correction of true multi-color spot counts to exclude randomly overlaid spots.